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official/nlp/modeling/networks/packed_sequence_embedding_test.py

Summary

Maintainability
A
1 hr
Test Coverage

Function test_network_creation has 28 lines of code (exceeds 25 allowed). Consider refactoring.
Open

  def test_network_creation(self, use_position_id, pack_multiple_sequences,
                            use_float16):
    """Validate that the Keras object can be created."""
    if use_float16:
      tf_keras.mixed_precision.set_global_policy('mixed_float16')
Severity: Minor
Found in official/nlp/modeling/networks/packed_sequence_embedding_test.py - About 1 hr to fix

    Similar blocks of code found in 7 locations. Consider refactoring.
    Open

        expected_config['initializer'] = tf_keras.initializers.serialize(
        tf_keras.initializers.get(expected_config['initializer']))
    Severity: Major
    Found in official/nlp/modeling/networks/packed_sequence_embedding_test.py and 6 other locations - About 35 mins to fix
    official/nlp/modeling/networks/albert_encoder_test.py on lines 161..162
    official/nlp/modeling/networks/albert_encoder_test.py on lines 163..164
    official/nlp/modeling/networks/funnel_transformer_test.py on lines 400..401
    official/nlp/modeling/networks/funnel_transformer_test.py on lines 402..403
    official/projects/roformer/roformer_encoder_test.py on lines 208..209
    official/projects/roformer/roformer_encoder_test.py on lines 210..211

    Duplicated Code

    Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

    Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

    When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

    Tuning

    This issue has a mass of 33.

    We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

    The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

    If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

    See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

    Refactorings

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